It is well known in the art to produce a three-dimensional (3D) point-cloud model of a physical entity. Such point-cloud can be produced by a probing device, which probes the surface of a physical object. Such probing can be tactile, optical, electro-magnetic, etc. The 3-D probing machine, namely a scanner, and typically a laser-scanner, creates a set of 3D points, namely a point-cloud, describing the shape and/or surface features of the object.
Creating a point-cloud for a large object or entity (these terms can be used in this documents interchangeably unless differentiated explicitly), such as a building or an urban environment, requires a large number of scans producing a large number of partial or local point-clouds, that have to be fused together to create a complete or global point-cloud of the entity. The terms object and entity, and the terms partial and local (with respect to point-cloud) can be used in this document interchangeably unless differentiated explicitly.
Typically, at least some of these scans require moving the scanner about the entity, therefore creating a problem of alignment of the plurality of local point-clouds to produce a complete and accurate global point-cloud.
Currently, the process of aligning local point-clouds is highly complex and requires massive processing power, human involvement, and time, and yet produces an imprecise global point-cloud.
There is thus a widely recognized need for, and it would be highly advantageous to have, a system and a method for fusing a plurality of local-point clouds into an accurate global point-cloud devoid of the above limitations.